27 results about "High risk environment" patented technology

This application discloses a spatial grid adaptive partitioning method, apparatus, device, and medium. The embodiment acquires multi-source heterogeneous 3D data of a target region and preprocesses the data to obtain the vertex density of each vertex within the target region. Based on the vertex coordinates, a pre-trained continuous environmental factor expression model predicts the multivariate environmental factors corresponding to each vertex. For any grid within the target region, based on the vertex density and multivariate environmental factors, it is determined whether the grid is to be partitioned. The grid to be partitioned is further partitioned based on the longest axis bisection strategy. Thus, by incorporating vertex density and environmental factors into the determination mechanism of the grid to be partitioned, and recursively partitioning through this mechanism, complex regions or high-risk environments obtain finer grids, while simple regions or low-risk environments maintain coarser grids, achieving non-uniform and differentiated adaptive partitioning.

The invention discloses a sky path planning design method and system based on an artificial intelligence algorithm, and relates to the technical field of unmanned aerial vehicles, and the technical scheme is characterized by comprising the following steps: obtaining environment data of a flight area of an unmanned aerial vehicle, and obtaining environment condition data of the flight area according to the environment data; setting a sub-planning area of the unmanned aerial vehicle according to the environmental condition data, and setting a planning parameter and a planning weight corresponding to the sub-planning area; real-time monitoring parameters of the sub-planning areas are collected, and sub-area planning coefficients of the sub-planning areas are obtained according to the real-time monitoring parameters, the planning parameters and the planning weights; performing comparative analysis on the sub-region planning coefficient and a preset planning coefficient threshold to obtain a first high-risk sub-planning region; obtaining a first high-risk area factor corresponding to the first high-risk sub-planning area; and obtaining the influence area factor of the first high-risk area factor according to the area correlation model, so that the unmanned aerial vehicle can actively avoid the path during planning, and is prevented from falling into a high-risk environment.

The invention discloses a nasal cavity biological protection preparation, a preparation method and application thereof and a nasal cavity intelligent protection system. The formulation comprises a mucin inspired polymer having a specific "brush-like bottleneck" molecular configuration, and an interpenetrating network formed from oppositely charged polysaccharides, which construct a three-dimensional hydrated gel by dynamic non-covalent cross-linking. The gel has the characteristics of shear thinning, strong mucous membrane adhesion and efficient particle interception. Temperature-sensitive, pH-sensitive or oxidation-reduction-sensitive intelligent microspheres can also be integrated in the preparation, so that responsiveness protection to the external environment is realized. The invention further provides an intelligent protection scheme comprising the preparation, a quantitative spraying device and a simple monitoring system. The preparation is safe and free of medicine, is suitable for preventing nasal cavity discomfort caused by air pollution, allergens, viruses and environment dryness, and is especially suitable for daily health protection under high-risk environment or extreme weather conditions.

The invention relates to the technical field of intelligent fire fighting, and discloses an intelligent fire fighting platform multi-equipment information fusion early warning method and system, and the method comprises the steps: continuously collecting the data of detection equipment in a clean room of a semiconductor manufacturing factory, and presetting and storing an abnormal signal sequence template containing ultrafine particles, chemical activity monitoring and traditional fire features; and early recognition of the atypical dangerous events is realized. According to the method, a real-time detection equipment data sequence is compared with an abnormal signal sequence template, the matching degree is obtained, and when the matching degree reaches a preset threshold value, it is judged that an atypical dangerous event exists, and early warning information is generated. According to the invention, the identification capability and the early warning timeliness of the intelligent fire-fighting platform on atypical dangerous events in high-risk environments such as semiconductor manufacturing factories can be obviously improved, and the equipment safety and the personnel health are effectively guaranteed.

The application discloses a kind of service-oriented unmanned equipment intelligent behavior conceptual model construction method, it is related to military field technical field, including the following steps: when unmanned equipment executes reconnaissance and strike task, carries optical, infrared and multispectral camera equipment, battlefield real-time video is continuously collected, through multispectral data acquisition, keep efficient target identification and tracking ability under various complex battlefield environment.The application improves target identification accuracy through multispectral data acquisition, real-time monitoring video stream extracts potential attack features, and with the help of deep learning model, attack hidden danger is efficiently identified, in high-risk environment, self-adapting adjustment detection strategy, enhance the response capability to hidden attack, ensure the accuracy and immediacy of tactical execution, to optimize identification efficiency, reduce the risk of misjudgment and missed detection, improve the utilization rate of combat resources, provide efficient, accurate, adaptive solution for the intelligent application of unmanned equipment.

The application discloses a kind of mobile security protection method and system based on AI dialogue and context perception, comprising: receiving the natural language request of user, the structured context object of the context information of device is generated by rule engine;Based on natural language request and context object, parse out user intent and at least one entity to be detected, to generate structured security instruction;Call corresponding threat analysis engine to carry out depth analysis and generate threat analysis result;According to threat analysis result, generate composite response containing natural language explanation and one-key execution operation option, call system interface to execute the protection action corresponding to threat analysis result;Collect the feedback data of user to composite response and continuously optimize parsing and threat analysis capability.The application analyzes device state, network environment and user behavior in real time, and the system can dynamically assess security risks, not only respond to user active query, but also actively push protection suggestions when detecting high-risk environment.

This application relates to a method, system, equipment, and medium for assessing the ESG resilience of heating facilities. The method includes: first, acquiring facility type data and dynamic environmental indicators; then, filtering and extracting environmental performance parameters and social demand indicators for heating scenarios to form a preliminary screening dataset; using a random forest algorithm to calculate the impact degree of dynamic environmental factors, obtaining a subset of high-risk environmental performance; extracting governance factor data and training a risk prediction model using a support vector machine algorithm; based on the equilibrium point output by the model, iteratively optimizing to obtain factor balance index data; simultaneously acquiring emission relationship index data and using a random forest algorithm for regression analysis to construct an emission relationship model; finally, extracting allocation fairness features, matching social demand to form an assessment framework, and integrating data to determine the adjustment results for the heating facility resilience assessment. This method can accurately reflect the actual resilience level of heating facilities and improve the scenario adaptability and generalization ability of the assessment method.

In one aspect, a computer-implemented method, includes a risk mitigation system receiving from a first sensor mounted on an autonomous vehicle, first sensor data. The first sensor data may be associated with a local magnetic field and is received periodically. The method may further include processing the first sensor data to identify an occurrence of an anomaly in the first sensor data. The occurrence may be associated with a time period. The risk mitigation system may request data from a second sensor mounted on the vehicle after identifying the anomaly. The method may further include receiving, from the second sensor, second sensor data. The second sensor data may be associated with an external environment of the autonomous vehicle. The risk mitigation system may process the second sensor data associated with the time period, and identify, based on the analyzed second sensor data and the anomaly, that the external environment is high-risk.

The invention provides a power transmission line tower grounding resistance unwiring-free measurement method and system, and belongs to the technical field of power transmission line operation maintenance and detection, and the method comprises the steps: constructing a tower equivalent loop model, employing a non-contact transformer to synchronously inject a test signal, and collecting multi-path response data, and establishing a multi-parameter complex equation set based on the Kirchhoff voltage law for solving, and finally judging the grounding resistance of the tower according to the order of magnitude relationship between the equivalent impedance and the grounding resistance. According to the invention, through the measurement method without wire releasing and auxiliary electrode bonding, the operation steps are simplified, the working efficiency is improved, personnel are prevented from working in a high-risk environment, and the working safety is improved; meanwhile, the portable design provides effective support for data real-time monitoring, online analysis and operation and maintenance decision on the basis of guaranteeing functionality, and the accuracy, efficiency and safety of power transmission line grounding resistance measurement are comprehensively optimized.

The invention discloses a multi-sensitive factor dynamic path optimization method for health protection, and the method comprises the steps: obtaining a user medical file and a medication record, generating a sensitive factor set of a user, and obtaining a candidate path set of user travel; dividing paths in the candidate path set into a plurality of segments according to a road network topological structure, and calculating segment health risk values of the paths based on the sensitive factor set; and constructing a three-dimensional cost function to calculate the total cost of the paths in the candidate path set, solving the path with the lowest total cost by adopting a three-layer path optimization engine, and starting an active protection measure when a health risk threshold is triggered. According to the invention, accurate modeling of individualized health features is realized; the method can remarkably reduce the individual health risk while guaranteeing the travel efficiency, improves the traffic decision intelligence and medical protection capability, and is suitable for the precise health management scene of chronic disease patients, specific sensitive people and high-risk environment travel.

The external monitoring frame comprises cabinet connecting rods, a first adjusting assembly, a second adjusting assembly and a monitoring assembly, the cabinet connecting rods are symmetrically arranged on the two sides of the face, needing to be monitored, of the cabinet, the first adjusting assembly is matched with a first adjusting groove in the cabinet connecting rods through a first sliding block, and the second adjusting assembly is matched with a second adjusting groove in the cabinet connecting rods through a second sliding block. The second adjusting assembly can move in the height direction of the cabinet to achieve preliminary longitudinal adjustment, the second adjusting assembly is rotationally and movably connected with the first adjusting assemblies on the two sides, the angle and the position can be flexibly changed, and the monitoring assembly is connected to the second adjusting assembly and right faces the face, needing to be monitored, of the cabinet; according to the utility model, a multi-dimensional adjustable modular structure is adopted, and the monitoring mechanism is laid along the cabinet connecting rod in a sliding manner, so that the position of the camera can be flexibly adjusted in space, cabinets of different specifications can be adapted, and effective monitoring of the to-be-monitored surfaces of the cabinets can be realized; therefore, the problems of high manual maintenance cost and high personnel safety risk of the machine station cabinet in a plateau unmanned area, a remote area and a high-risk environment are effectively solved.

This disclosure relates generally to the fields of data management, collection, conditioning, and curation for driving advanced data analytics, artificial intelligence (AI) and machine learning (ML), and more particularly to contextualized data collection and curation for adaptive learning and for training advanced autonomy models in multi-actor applications in dynamic high-risk environments (e.g., multi-domain socio-technical work environments (MSWEs))—from mission control to military operations, from operating rooms to racecar engineering—where experts must effectively employ technologies to drive data-informed decisions based on situational assessment. This disclosure provides enabling technology for ML-based autonomy solutions to effectively utilize current and emerging analysis and debrief tools across relevant domains, which necessitates an inclusion of formal data contextualization processes. These processes support training the next generation of experts and simultaneously generate relevant contextually labeled data for adaptive learning and training advanced ML models for event-driven autonomy operations.

This invention discloses a protection and control method and system for energy storage converter testing under extreme environments. The method includes calibrating the parameters of a multiphysics reduced-order simulation model based on measured performance data to obtain a calibrated multiphysics reduced-order simulation model; embedding a device-level performance degradation proxy model into the calibrated multiphysics reduced-order simulation model to obtain a system-level simulation model; inputting environmental parameter samples into the system-level simulation model for simulation, obtaining risk assessment results based on the performance simulation result set, and selecting at least one high-risk environmental parameter combination; obtaining corresponding physical test cases, driving test equipment to perform physical extreme environment tests on the energy storage converter, comparing the measured results with the prediction results obtained by the system-level simulation model based on the corresponding high-risk environmental parameter combination simulation, and optimizing the parameters of the multiphysics reduced-order simulation model and the device-level performance degradation proxy model to ensure the reliability of the energy storage converter operating under extreme environments.

Systems and processes are provided for Robust Detection of Accuracy Loss in Explainable AI (XAI) systems using Quantum Entanglement and Model-Matrix Frameworks. The system integrates quantum entanglement principles to detect anomalies in model computations, flagging poisoned data and computational deviations. It uses hash-key tracking not only for final outputs but for the methods used, ensuring any manipulation in processing steps is detected. Real-time continuous scanning monitors for cyberattacks, while a traceability matrix tracks data lineage. The system employs swarm intelligence for decentralized task distribution and auditing, ensuring scalability in large data environments. Additionally, the self-healing capability allows the system to automatically correct identified anomalies, maintaining the reliability of AI outputs. This comprehensive system ensures the integrity, security, and transparency of AI computations, addressing accuracy loss due to both external threats and internal data corruption in high-stakes environments.

The invention discloses a cloud edge cooperative driving multi-agent safety reinforcement learning power distribution network reconstruction method, and relates to the technical field of power distribution network intelligent scheduling. Comprising the following steps: firstly, establishing a multi-feeder power distribution network reconstruction model; secondly, under the framework of cloud centralized training and side end decentralized execution, dividing multiple agents according to physical connection of a feeder group and an actual power grid topology, and designing a Markov decision process with global shared rewards; then, by introducing a hard constraint of single-cycle accumulated safety cost, based on a Lagrange optimization framework, safety reinforcement learning modeling is realized so as to enhance robustness of a reconstruction strategy in a high-risk environment. According to the method, the reconstruction safety and the operation robustness of the complex power distribution network under the high-risk working condition are remarkably improved.

The invention relates to a movable automatic medicine conveying system, and belongs to the technical field of automation. The system comprises an environment sensing subsystem; an intelligent medicine bin control subsystem; a mechanical transmission subsystem; a wireless communication subsystem; a solar charging subsystem; an environment monitoring subsystem; the system comprises a multi-band interference subsystem, an all-terrain mobile chassis subsystem and a mechanical transmission subsystem. Wherein the all-terrain mobile chassis subsystem is integrated with other subsystems, each subsystem is controlled by the MCU central processing module, and the MCU central processing module controls the all-terrain mobile chassis subsystem through a wire interface. The system can be used in areas where manpower or traditional vehicles cannot pass through, and the change of drugs from path dependence to global reachability is realized; the dependence on the operation of professionals is obviously reduced; therefore, the system is especially suitable for high-risk environments such as battlefields and the like. And obvious advantages are shown in the aspects of operation cost and sustainability.

The invention relates to a comprehensive display localization ruggedized computer based on dual-computer hot switching, and belongs to the technical field of computers. The ruggedized computer comprises a VPX case, a master computing processing module, a slave computing processing module, a comprehensive display module, a power supply module, a bus bottom plate, a flexible plate and an aviation plug board, the ruggedized computer supports embedding of two computing processing boards as a master computing processing module and a slave computing processing module to form a dual-computer master / slave working mode, and an external input / output device is shared through a comprehensive display module. Through a dual-computer switching mechanism, the reliability and the fault-tolerant capability of the system are remarkably improved, and the method is suitable for a high-risk environment. The extended comprehensive display function meets the requirements of complex data processing and multi-task display, and the user experience is improved; the high-performance network switching function ensures the stability and safety of communication, and is suitable for complex environments.

The application discloses a server identity authentication method, a client identity authentication method, a server, a client, a dynamic authentication system, a computer device and a computer program product. The server identity authentication method comprises the following steps: receiving a login request sent by a client and containing a user credential; performing verification processing on the user credential to obtain a verification result; when the verification result is successful, performing risk assessment to obtain a risk assessment result; when the risk assessment result is a high-risk environment, temporarily storing state information of successful verification and sending an authentication failure response message to the client, the authentication failure response message being consistent with a real authentication failure response in preset characteristics; receiving environment verification information; performing identity authenticity verification based on the environment verification information; and when the identity verification result is passed, returning an authentication success response to the client, the authentication failure response message being consistent with the real authentication failure response in the preset characteristics, so that runtime fraud prevention is realized and security is improved.

Dynamic Digital Immune Systems / Processes (DDIS) improve data integrity and quality in Explainable AI (XAI) systems. Operating in real time, it monitors data from distributed sources during federated training, detecting and flagging corrupted, poisoned, or low-quality data with dynamic anomaly detection algorithms. The system includes automated data cleaning to remove redundant and irrelevant data, enhancing AI model performance. It features dynamic encryption that adapts to data sensitivity, ensuring robust security. Swarm intelligence-based task distribution allows decentralized auditing of data integrity, while a traceability matrix tracks data lineage for transparency. The DDIS also incorporates a self-healing mechanism that automatically corrects identified anomalies, ensuring continuous reliability of AI outputs. This comprehensive system protects against data corruption, enhances processing efficiency, and safeguards the accuracy and integrity of XAI systems in high-stakes environments.

The application discloses a kind of safety control system and method of explosion-proof automatic guided vehicle based on security tree logic, system is obtained by acquisition module real-time acquisition vehicle body operation and environmental parameter, adopt the two-way reasoning mechanism of safety degree from bottom to top layer by layer calculation, from top to bottom reverse positioning risk source, root node safety degree and the node combination that causes target safety condition to weaken are jointly used as safety judgment basis, and set early warning speed limit, controlled parking and explosion-proof isolation, emergency power-off and energy isolation three-level response.The application can self-adaptively adjust node weight and credibility coefficient, suppress sensor misjudgment, realize multivariate coupling risk accurate identification, automatically guide safety state when fault, significantly improve the running safety, reliability and anti-interference ability of explosion-proof AGV in high-risk environment, adapt to petrochemical, coal mine, military and other explosion-proof scenes.

The utility model discloses a kind of filling air return shaft ladder platform devices suitable for downward filling mining method, belong to underground filling technical field, the utility model includes filling air return shaft, several platforms are arranged inside the filling air return shaft, ladder is arranged between adjacent two platforms, the platform is mainly fixedly connected in air return shaft inboard wall by bolt, avoid the safety risk caused by welding in high altitude limited space, the upper end of the ladder is passed through U type hook, the lower end is passed through second support frame, stably fixed between two platforms, dismounting is convenient and flexible, the problem of long operation time of original welding method is solved, overall design improves installation efficiency and the convenience of maintenance, suitable for the safety operation demand of high-risk environment in well.

This invention discloses an emergency escape window, comprising: a window body, the main frame of which is made of reinforced steel or special alloy material and equipped with a multi-layer composite glass panel; a folding airbag, integrated and stored in the lower or side frame of the window body, made of high-strength, flame-retardant, and tear-resistant composite plastic, the airbag being highly compressed when not deployed, and designed as a slide with protective sidewalls; and a window-breaking ejection button located on the surface of the window body. This emergency escape window, by combining robust explosion-proof performance with a second-level response escape route, provides users with an independent, reliable, and rapid lifeline in emergencies, greatly improving the survival rate in high-risk environments and effectively reducing casualties. The inflatable slide provides a buffered and guided descent path, avoiding the impact injuries from high-altitude jumps and potential stampedes in chaos.

The utility model relates to the technical field of mining industry, and discloses a mineral aggregate conveying device which comprises a supporting plate, rolling rollers movably connected with the supporting plate are inserted between the left end and the right end of the supporting plate, a motor is fixed to one end of the supporting plate, a rotating shaft of the motor is fixedly connected with the rolling rollers, and the outer surfaces of the two rolling rollers are sleeved with a conveying belt. Through combination of the scraping assembly and the cleaning assembly, mineral aggregate residues on the surface of the conveying belt can be cleaned in time, the workload of manual cleaning and the downtime of equipment are reduced, meanwhile, the clean state of the conveying device is continuously kept, abrasion of the conveying belt is greatly reduced, the service life of the equipment is prolonged, and the production cost is reduced. Compared with the prior art, the conveying device has the advantages that maintenance and replacement cost is reduced, blockage caused by accumulation of mineral aggregate is reduced, the conveying device can keep stable conveying speed, overall production efficiency is improved, manual cleaning work in a high-risk environment is avoided, and operation risks and potential safety hazards are reduced.

The invention belongs to the technical field of protective masks, and discloses an exterior syndrome relieving, cold dispelling, toxin removing and antibacterial mask. The mask mainly comprises a mask body, ear hanging ropes and a filtering opening, and is characterized in that a dual drug delivery system integrating a humidity response type regulating and releasing film and a manual pressing type emergency drug release bin is integrated. The adjustable release film can adaptively release traditional Chinese medicine active ingredients according to breathing humidity, so that daily intelligent protection is realized; the emergency drug release bin can be actively triggered by a user to quickly release high-concentration drugs to cope with a high-risk environment. The device is further provided with a linkage mechanism which can stimulate the controlled release film to generate microcracks in an emergency mode so as to accelerate drug diffusion, and synergistic interaction is achieved. Meanwhile, the medicine bin is of a detachable design and a one-way valve structure, replacement is convenient, and pollution can be prevented. The defects that a traditional Chinese medicine mask is uncontrollable in medicine release and single in protection mode are overcome, and a full-scene and intelligent solution scheme from daily health care to emergency protection is provided.

The invention belongs to the technical field of environmental new pollutant screening, and particularly relates to a method for screening high-risk environmental chemicals related to bad health outcome, which comprises the following steps: S1, blood sample pretreatment: taking human blood as a sample, extracting environmental chemicals through liquid-liquid extraction, and sequentially performing concentration, methanol redissolution, low-temperature freezing and centrifugal treatment to obtain a blood sample; collecting supernate, adding an isotope labeling internal standard, and diluting to a set volume to obtain a sample to be analyzed; s2, mass spectrum detection: adopting an ultra-high performance liquid chromatography-tandem mass spectrum system to collect primary and secondary mass spectrum information of the chemicals in the sample to be analyzed in a positive and negative ion mode. Through systematic design of blood pretreatment, mass spectrometric detection, suspicious object database construction, grading screening and high-risk identification, the technical problems that a traditional screening method is narrow in targeted analysis coverage range, insufficient in non-targeted analysis accuracy and lack of pertinence in mixed exposure risk assessment are effectively solved.

Dynamic Digital Immune Systems / Processes (DDIS) improve data integrity and quality in Explainable AI (XAI) systems. Operating in real time, it monitors data from distributed sources during federated training, detecting and flagging corrupted, poisoned, or low-quality data with dynamic anomaly detection algorithms. The system includes automated data cleaning to remove redundant and irrelevant data, enhancing AI model performance. It features dynamic encryption that adapts to data sensitivity, ensuring robust security. Swarm intelligence-based task distribution allows decentralized auditing of data integrity, while a traceability matrix tracks data lineage for transparency. The DDIS also incorporates a self-healing mechanism that automatically corrects identified anomalies, ensuring continuous reliability of AI outputs. This comprehensive system protects against data corruption, enhances processing efficiency, and safeguards the accuracy and integrity of XAI systems in high-stakes environments.